nasa/ExoMiner
Automating the vetting and validation of planet candidates from photometry survey missions - Kepler and TESS - using deep learning methods
Implements the ExoMiner++ convolutional neural network architecture for transit signal classification on preprocessed light curve features extracted from Kepler/TESS FITS files. The modular pipeline integrates data preprocessing, hyperparameter optimization, cross-validation, and inference stages, with containerized deployment via Podman for streamlined execution from raw TIC IDs to prediction scores.
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62
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16
Language
Python
License
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Category
Last pushed
Feb 03, 2026
Commits (30d)
0
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